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Addressing Academic Dishonesty in Higher Education: A Systematic Review of Generative AI's Impact

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Title: Addressing Academic Dishonesty in Higher Education: A Systematic Review of Generative AI's Impact
Language: English
Authors: Ramesh Chander Sharma (ORCID 0000-0002-1371-1157), Suman Kalyan Panja (ORCID 0000-0002-9097-4938)
Source: Open Praxis. 2025 17(2):251-269.
Availability: International Council for Open and Distance Education. Lilleakerveien 23, 0283 Oslo, Norway. Tel: +47-22-06-26-30; Fax: +47-22-06-26-31; e-mail: icde@icde.org; Web site: https://openpraxis.org/
Peer Reviewed: Y
Page Count: 19
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Ethics, Plagiarism, Cheating, Higher Education, Technology Uses in Education, Integrity
ISSN: 1369-9997
2304-070X
Abstract: Generative Artificial Intelligence (GAI) introduces new opportunities for society. While some universities have adopted GAI with a more hostile stance, others have done so with a more progressive perspective. In light of this contradiction, the main query is what is causing this controversy. The ethical issues surrounding GAI and academic dishonesty in higher education, however, are the special focus of the current study. 23 previous studies published between 2022 and 2024 served as the foundation for this systematic literature review (SLR). Three educational theories--digital innovation, diffusion of innovation, and thing ethnography--form the basis of this study. A content analysis of the research corpus was done to find important themes. The findings are synthesized by employing a novel thematic analysis approach. Research questions determine the feasibility of academic integrity in the face of plagiarism or cheating. Considering GAI, existing curricula and assessment procedures show room for modification. There are technological, institutional, or individual issues around academic dishonesty. Furthermore, problems with legitimacy and ethics are also evident. The current guidelines are consistent rather than cohesive. Based on this idea, the current researchers proposed a thorough set of guidelines for the education community. The results of this study are thought to offer comprehensive insights into addressing academic dishonesty in higher education, especially in the age of GAI. The proposed ethical framework explains how it can theoretically contribute to higher education.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1481213
Database: ERIC
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  Data: Addressing Academic Dishonesty in Higher Education: A Systematic Review of Generative AI's Impact
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  Data: <searchLink fieldCode="AR" term="%22Ramesh+Chander+Sharma%22">Ramesh Chander Sharma</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1371-1157">0000-0002-1371-1157</externalLink>)<br /><searchLink fieldCode="AR" term="%22Suman+Kalyan+Panja%22">Suman Kalyan Panja</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9097-4938">0000-0002-9097-4938</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Open+Praxis%22"><i>Open Praxis</i></searchLink>. 2025 17(2):251-269.
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  Data: International Council for Open and Distance Education. Lilleakerveien 23, 0283 Oslo, Norway. Tel: +47-22-06-26-30; Fax: +47-22-06-26-31; e-mail: icde@icde.org; Web site: https://openpraxis.org/
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  Data: 19
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  Data: Journal Articles<br />Information Analyses
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Plagiarism%22">Plagiarism</searchLink><br /><searchLink fieldCode="DE" term="%22Cheating%22">Cheating</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Integrity%22">Integrity</searchLink>
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  Data: Generative Artificial Intelligence (GAI) introduces new opportunities for society. While some universities have adopted GAI with a more hostile stance, others have done so with a more progressive perspective. In light of this contradiction, the main query is what is causing this controversy. The ethical issues surrounding GAI and academic dishonesty in higher education, however, are the special focus of the current study. 23 previous studies published between 2022 and 2024 served as the foundation for this systematic literature review (SLR). Three educational theories--digital innovation, diffusion of innovation, and thing ethnography--form the basis of this study. A content analysis of the research corpus was done to find important themes. The findings are synthesized by employing a novel thematic analysis approach. Research questions determine the feasibility of academic integrity in the face of plagiarism or cheating. Considering GAI, existing curricula and assessment procedures show room for modification. There are technological, institutional, or individual issues around academic dishonesty. Furthermore, problems with legitimacy and ethics are also evident. The current guidelines are consistent rather than cohesive. Based on this idea, the current researchers proposed a thorough set of guidelines for the education community. The results of this study are thought to offer comprehensive insights into addressing academic dishonesty in higher education, especially in the age of GAI. The proposed ethical framework explains how it can theoretically contribute to higher education.
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        StartPage: 251
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      – SubjectFull: Ethics
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      – SubjectFull: Plagiarism
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      – SubjectFull: Cheating
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      – SubjectFull: Higher Education
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      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Integrity
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